1. Field of the Invention
The present invention relates to a method for the positioning of electromagnetic sensors or transmitters in an array. It applies in particular to the optimization of plane or linear antenna arrays.
2. Discussion of the Background
An antenna is used to transmit and receive electromagnetic energy. In certain circumstances, a single antenna is enough to receive a signal that has undergone a little scrambling and that has been subjected to a few echoes. In this case, the radar is a parabolic reflector or a single dipole. However, radar applications are increasingly requiring high-gain antennas and the verification of a set of directional constraints. These constraints can be set for example by an antijamming operation using a fixed jammer. The constraints may also be variable, as in the case for example of the shifting of the main beam to obtain points of aim. One example of variable constraints relates for example to electronic scanning radars where the main beam moves electronically to sweep through a solid angle.
To satisfy these constraints, there is a known way of using antenna arrays. An antenna array is a graph whose nodes are elementary electromagnetic sensors. It enables the simultaneous processing of the signals coming from several angular directions. Unlike in the case of a single antenna with a limited frequency band and directivity, an antenna array has a modifiable pattern, in particular with the amplitude and/or phase weighting that is applied to each element. These weighting values can be combined to give preference to signals over possible interference, jamming and noise.
The synthesizing of a radar pattern includes in finding the weighting values that correspond to a set of given specifications. The synthesis of a pattern for an antenna array furthermore includes in finding an arrangement of the sensors by which the given constraints can be verified. In general, to meet these specifications, a curve that corresponds to an optimal pattern is defined, and it is sought to approach this curve, called a template, by varying the weighting values and the positions of the sensors.
The pattern thus does not depend only on the weighting values assigned to each element. It depends also on the frequency at which the array functions and on the positions of the elements of the antenna, especially the sensors. The problem that seems to be the most difficult and least resolved is how to search for the optimal geometry of an antenna given a series of constraints. This search must be guided by a desire to reduce the complexity of the array and its processing.
Uniformly distributed linear arrays have been designed, and there are known methods providing satisfactory solutions. However, the high cost of the elementary sensors has been a motivation behind the designing of non-uniform linear arrays, built either by the elimination of sensors from a uniform array, or by the pseudo-random positioning of sensors. In the latter case, obtaining the optimal pattern by varying the weighting values requires very high-level computations that greatly depend on the geometry, the frequency of reception and the desired template. In addition, more highly restrictive antijamming constraints and the advent of electronic scanning radars that have made it necessary to develop plane antenna arrays, are even further complicating the search for an optimal pattern.
The synthesis of an antenna array pattern thus includes finding an arrangement of the electromagnetic sensors and a configuration of the weighting values that provide for the verification of given constraints. In particular, it entails problems of optimization under constraints related to the positioning of the sensors in linear, plane or thinned arrays. The constraints may be highly varied. They may be, for example, limits on the number of sensors or constraints related to the electromagnetic coupling of the sensors. There are known methods of optimization that work on a continuous field and bring satisfactory solutions. However, the non-convexity and the non-continuity of certain constraints makes it difficult to implement them.